Missigness before removing buffer
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missingness plots, missing values: 14853 out of 113400 (13.10%)
Missingness after removing buffer
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missingness plots, missing values: 10227 out of 90720 (11.27%)
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features filtered, 50.00%, 39 of 630 removed
Missingness after filtering metabolites with more than 50% missing values per group
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missingness plots, missing values: 6331 out of 85104 (7.44%)
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sample boxplot, aes: color=Buffer
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sample boxplot, aes: color=tissue
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quotient normalization based on 36 reference samples and 511 variables: ~
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quotient normalization based on 36 reference samples and 511 variables: Buffer == “80% Meth + 20% H2O”
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dilution factor plot, ‘Buffer’
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sample boxplot, aes: color=Buffer
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log2.000000
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sample boxplot, aes: color=Buffer
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flagged 0 univariate outliers
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Dataset info: 144 samples, 591 features; 25 sample annotation fields, 10 feature annotation fields
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Data exported to Excel file ‘PreprocessedData.xlsx’
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UMAP, label_col: , aes: color=Buffer, size=2.5
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Heatmap of assay data.
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UMAP, label_col: , aes: color=tissue, size=2.5
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Heatmap of assay data.
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PCA, scores, label_col: , aes: color=Buffer, shape=tissue, size=2.5
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pathway aggregation by ‘Class’, 22 pathway scores generated
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univariate lm, ~Buffer
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Multiple testing correction of ‘Buffer pw’ using ‘BH’
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‘Buffer pw’ info
Samples: 50% Meth + 50% H2O: 36, 50% Meth + 50% PBS: 36, 80% Meth + 20% H2O: 36, 80% Meth + 20% PBS: 36 /// features: p.adj < 0.05, 7 of 22
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P-value histograms for Buffer pw
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Feature
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univariate lm, ~tissue
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Multiple testing correction of ‘Tissue pw’ using ‘BH’
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‘Tissue pw’ info
Samples: fat: 48, liver: 48, muscle: 48 /// features: p.adj < 0.05, 21 of 22
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P-value histograms for Tissue pw
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Feature
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Pheatmap of stat results. Colors represent (sign(statistic) * -log10(p.adj)))
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comparison plot between ‘Buffer pw’ and ‘Tissue pw’